Business typically requires a multitude of businesses to work together, wherein there are many involved in a supply chain, many acting as service providers, advisors, brokers and of course customers to pay for it all. To be successful, a business is required to identify and assemble a network appropriate to service the business at each point. In many cases an organization will have an established network; however, there is commonly a need for an organization to locate a new supplier, partner, client, or buyer. These can be easily found with reference to an Internet search engine or phone directory. Dedicated websites currently exist to provide a user with a list of businesses according to a particular industry or service/product offered.
However, this does not help the searcher determine which potential supplier/client is the best or most relevant to themselves. By human nature it is common to ask who is used and trusted by other businesses that are respected by the searcher.
This information is usually only known to those with years of experience, are well connected or who have access to specialist business directories. In some cases relationships can be determined from online or physical records but it is not always possible to know the nature, trust, strength, or present activity of the relationship. The search is typically made against some criteria such as location or sector. Even with knowledge of these relationships, it is not a simple matter to search by certain criteria, filter certain categories or weigh large amounts of such data.
Existing platforms attempt to solve this problem by creating searchable directories of businesses and/or providing reviews from other users. In some instances, the list is ranked according to a metric such as size or revenue. In these cases the user must judge what review or metric might be suitable for their own business. Most recently, classes of programs called Recommendation Systems look for similarity between users to recommend products and services.
The present inventors have appreciated an opportunity to address these issues by creating a database of business relationships, whereby the strength of such relationships and similarity of businesses rather than users provides a basis for making a recommendation of an organization, products and services.